The exploitative segregation of plant roots

Abstract

Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world’s vegetation carbon pool. Study of belowground competition, unlike aboveground shoot competition, is hampered by our inability to observe roots. We developed a consumer-resource model based in game theory that predicts the root density spatial distribution of individual plants and tested the model predictions in a greenhouse experiment. Plants in the experiment reacted to neighbors as predicted by the model’s evolutionary stable equilibrium, by both overinvesting in nearby roots and reducing their root foraging range. We thereby provide a theoretical foundation for belowground allocation of carbon by vegetation that reconciles seemingly contradictory experimental results such as root segregation and the tragedy of the commons in plant roots.

No neighbour-induced increase in root growth of soybean and sunflower in mesh-divider experiments after controlling for nutrient concentration and soil volume

“…a distance-related cost of nutrient transport from soil location to plant stem) is incorporated in Gersani et al ’s original model, the new model predicts that plants should overproduce (or underproduce) roots in nutrient patches that are closer to (or further away from) them than to neighbours, due to a relative lower (or higher) cost of nutrient transportation in shorter (or longer) distance than neighbours. This prediction appears to be supported by some empirical observations ( Cabal et al 2020 ; Lepik et al 2021 ). Their findings indicate that interplant distance (or plant density) is a critical component determining root foraging behaviours of plants in resource competition ( Cabal et al 2020 ), and suggest that an evaluation of root production at whole-plant level or over large spatial scales may lead to incomplete- even miss-understanding of plant–plant root interaction ( Semchenko 2020 ).…”

“…This prediction appears to be supported by some empirical observations ( Cabal et al 2020 ; Lepik et al 2021 ). Their findings indicate that interplant distance (or plant density) is a critical component determining root foraging behaviours of plants in resource competition ( Cabal et al 2020 ), and suggest that an evaluation of root production at whole-plant level or over large spatial scales may lead to incomplete- even miss-understanding of plant–plant root interaction ( Semchenko 2020 ). This also suggests that the differences in results between Gersani et al and us may reflect a difference in spatial pattern of nutrient-transportation cost for plants in resource competition between the two studies (i.e.…”

“…A recent study by Cabal et al (2020) showed that when spatial dimension (i.e. a distance-related cost of nutrient transport from soil location to plant stem) is incorporated in Gersani et al ’s original model, the new model predicts that plants should overproduce (or underproduce) roots in nutrient patches that are closer to (or further away from) them than to neighbours, due to a relative lower (or higher) cost of nutrient transportation in shorter (or longer) distance than neighbours.…”

“…The potential selective advantage of resource investment in root production for a plant engaged in root competition can be analysed using evolutionary game theory ( Gersani et al 2001 ; McNickle and Dybzinski 2013 ; Cabal et al 2020 ). Game-theoretical models predict that when resource investment in root production of a plant is based on an assessment of cost and benefit balance in response to the decline of nutrient availability caused by the consumption from both the plant and its neighbours, the plant should over-proliferate roots to an extent that exceeds the optimal level for maximized performance (e.g.…”

Lianas Significantly Reduce Aboveground and Belowground Carbon Storage: A Virtual Removal Experiment

“…More generally, the fine-root dynamics in the liana removal experiment and their seasonal fluctuations (Cordeiro et al, 2020) should be investigated in more detail in future experimental studies. Such experiments should allow disentangling two contrasting situations: there are either more (fine) roots in liana removal plots because of the faster tree growth (as simulated in ED2) or there are more (fine) roots in control plots because of the stronger ongoing competition for below ground resources (Cabal et al, 2020). These examples of model-enabled, field-testable hypotheses are a good illustration of an efficient model-data fusion approach: model simulations calibrated on field datasets generated research questions whose evaluation could help refine modeled plant and soil processes.…”